Overview

Dataset statistics

Number of variables44
Number of observations271
Missing cells2353
Missing cells (%)19.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory99.6 KiB
Average record size in memory376.5 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-18010/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
여성종사자수 is highly imbalanced (54.8%)Imbalance
영업장주변구분명 is highly imbalanced (66.4%)Imbalance
총인원 is highly imbalanced (72.2%)Imbalance
본사종업원수 is highly imbalanced (51.7%)Imbalance
공장사무직종업원수 is highly imbalanced (72.2%)Imbalance
공장판매직종업원수 is highly imbalanced (72.2%)Imbalance
공장생산직종업원수 is highly imbalanced (72.2%)Imbalance
건물소유구분명 is highly imbalanced (77.2%)Imbalance
인허가취소일자 has 271 (100.0%) missing valuesMissing
폐업일자 has 152 (56.1%) missing valuesMissing
휴업시작일자 has 271 (100.0%) missing valuesMissing
휴업종료일자 has 271 (100.0%) missing valuesMissing
재개업일자 has 271 (100.0%) missing valuesMissing
전화번호 has 46 (17.0%) missing valuesMissing
소재지면적 has 43 (15.9%) missing valuesMissing
도로명주소 has 29 (10.7%) missing valuesMissing
도로명우편번호 has 30 (11.1%) missing valuesMissing
좌표정보(X) has 11 (4.1%) missing valuesMissing
좌표정보(Y) has 11 (4.1%) missing valuesMissing
다중이용업소여부 has 67 (24.7%) missing valuesMissing
시설총규모 has 67 (24.7%) missing valuesMissing
전통업소지정번호 has 271 (100.0%) missing valuesMissing
전통업소주된음식 has 271 (100.0%) missing valuesMissing
홈페이지 has 271 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 16 (5.9%) zerosZeros
시설총규모 has 39 (14.4%) zerosZeros

Reproduction

Analysis started2024-05-11 05:45:04.991786
Analysis finished2024-05-11 05:45:06.406446
Duration1.41 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
3080000
271 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3080000
2nd row3080000
3rd row3080000
4th row3080000
5th row3080000

Common Values

ValueCountFrequency (%)
3080000 271
100.0%

Length

2024-05-11T05:45:06.606536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:06.904397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3080000 271
100.0%

관리번호
Text

UNIQUE 

Distinct271
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-05-11T05:45:07.276666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5962
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique271 ?
Unique (%)100.0%

Sample

1st row3080000-105-1990-00033
2nd row3080000-105-1990-00034
3rd row3080000-105-1990-00036
4th row3080000-105-1990-00037
5th row3080000-105-1990-00038
ValueCountFrequency (%)
3080000-105-1990-00033 1
 
0.4%
3080000-105-2011-00001 1
 
0.4%
3080000-105-2011-00003 1
 
0.4%
3080000-105-2011-00004 1
 
0.4%
3080000-105-2011-00005 1
 
0.4%
3080000-105-2011-00006 1
 
0.4%
3080000-105-2011-00007 1
 
0.4%
3080000-105-2011-00008 1
 
0.4%
3080000-105-2011-00009 1
 
0.4%
3080000-105-2011-00010 1
 
0.4%
Other values (261) 261
96.3%
2024-05-11T05:45:08.121469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2993
50.2%
- 813
 
13.6%
1 506
 
8.5%
5 385
 
6.5%
3 345
 
5.8%
2 330
 
5.5%
8 310
 
5.2%
9 142
 
2.4%
4 58
 
1.0%
6 51
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5149
86.4%
Dash Punctuation 813
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2993
58.1%
1 506
 
9.8%
5 385
 
7.5%
3 345
 
6.7%
2 330
 
6.4%
8 310
 
6.0%
9 142
 
2.8%
4 58
 
1.1%
6 51
 
1.0%
7 29
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 813
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5962
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2993
50.2%
- 813
 
13.6%
1 506
 
8.5%
5 385
 
6.5%
3 345
 
5.8%
2 330
 
5.5%
8 310
 
5.2%
9 142
 
2.4%
4 58
 
1.0%
6 51
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5962
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2993
50.2%
- 813
 
13.6%
1 506
 
8.5%
5 385
 
6.5%
3 345
 
5.8%
2 330
 
5.5%
8 310
 
5.2%
9 142
 
2.4%
4 58
 
1.0%
6 51
 
0.9%

인허가일자
Date

Distinct211
Distinct (%)77.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum1990-03-02 00:00:00
Maximum2023-03-28 00:00:00
2024-05-11T05:45:08.561145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:45:09.011847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing271
Missing (%)100.0%
Memory size2.5 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
1
152 
3
119 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 152
56.1%
3 119
43.9%

Length

2024-05-11T05:45:09.451063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:09.767574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 152
56.1%
3 119
43.9%

영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
영업/정상
152 
폐업
119 

Length

Max length5
Median length5
Mean length3.6826568
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 152
56.1%
폐업 119
43.9%

Length

2024-05-11T05:45:10.288605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:10.618339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 152
56.1%
폐업 119
43.9%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
1
152 
2
119 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 152
56.1%
2 119
43.9%

Length

2024-05-11T05:45:11.012345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:11.383106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 152
56.1%
2 119
43.9%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
영업
152 
폐업
119 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row영업
3rd row영업
4th row영업
5th row영업

Common Values

ValueCountFrequency (%)
영업 152
56.1%
폐업 119
43.9%

Length

2024-05-11T05:45:11.918161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:12.551529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 152
56.1%
폐업 119
43.9%

폐업일자
Date

MISSING 

Distinct110
Distinct (%)92.4%
Missing152
Missing (%)56.1%
Memory size2.2 KiB
Minimum1998-12-19 00:00:00
Maximum2024-03-04 00:00:00
2024-05-11T05:45:13.107103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:45:13.771183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing271
Missing (%)100.0%
Memory size2.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing271
Missing (%)100.0%
Memory size2.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing271
Missing (%)100.0%
Memory size2.5 KiB

전화번호
Text

MISSING 

Distinct218
Distinct (%)96.9%
Missing46
Missing (%)17.0%
Memory size2.2 KiB
2024-05-11T05:45:14.417265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.755556
Min length2

Characters and Unicode

Total characters2420
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique211 ?
Unique (%)93.8%

Sample

1st row02 9932631
2nd row02 904 0572
3rd row02 9033231
4th row02 9896017
5th row02 9963501
ValueCountFrequency (%)
02 214
40.8%
989 7
 
1.3%
997 7
 
1.3%
981 6
 
1.1%
986 5
 
1.0%
987 5
 
1.0%
900 5
 
1.0%
984 4
 
0.8%
980 4
 
0.8%
944 3
 
0.6%
Other values (243) 265
50.5%
2024-05-11T05:45:15.594747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 407
16.8%
393
16.2%
9 351
14.5%
2 337
13.9%
8 196
8.1%
1 147
 
6.1%
7 126
 
5.2%
6 124
 
5.1%
5 123
 
5.1%
3 118
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2027
83.8%
Space Separator 393
 
16.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 407
20.1%
9 351
17.3%
2 337
16.6%
8 196
9.7%
1 147
 
7.3%
7 126
 
6.2%
6 124
 
6.1%
5 123
 
6.1%
3 118
 
5.8%
4 98
 
4.8%
Space Separator
ValueCountFrequency (%)
393
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2420
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 407
16.8%
393
16.2%
9 351
14.5%
2 337
13.9%
8 196
8.1%
1 147
 
6.1%
7 126
 
5.2%
6 124
 
5.1%
5 123
 
5.1%
3 118
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 407
16.8%
393
16.2%
9 351
14.5%
2 337
13.9%
8 196
8.1%
1 147
 
6.1%
7 126
 
5.2%
6 124
 
5.1%
5 123
 
5.1%
3 118
 
4.9%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct175
Distinct (%)76.8%
Missing43
Missing (%)15.9%
Infinite0
Infinite (%)0.0%
Mean81.42864
Minimum0
Maximum808.48
Zeros16
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T05:45:16.169915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19.8
median26.68
Q3107.9725
95-th percentile286.945
Maximum808.48
Range808.48
Interquartile range (IQR)98.1725

Descriptive statistics

Standard deviation134.93118
Coefficient of variation (CV)1.6570481
Kurtosis13.029782
Mean81.42864
Median Absolute Deviation (MAD)21.705
Skewness3.3791469
Sum18565.73
Variance18206.422
MonotonicityNot monotonic
2024-05-11T05:45:16.809450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 16
 
5.9%
16.5 6
 
2.2%
66.0 4
 
1.5%
7.0 4
 
1.5%
13.0 4
 
1.5%
5.0 3
 
1.1%
13.2 3
 
1.1%
9.9 3
 
1.1%
12.0 3
 
1.1%
6.9 2
 
0.7%
Other values (165) 180
66.4%
(Missing) 43
 
15.9%
ValueCountFrequency (%)
0.0 16
5.9%
3.74 1
 
0.4%
4.0 1
 
0.4%
4.16 1
 
0.4%
4.4 1
 
0.4%
4.59 1
 
0.4%
4.7 1
 
0.4%
4.94 1
 
0.4%
4.95 2
 
0.7%
5.0 3
 
1.1%
ValueCountFrequency (%)
808.48 1
0.4%
776.98 1
0.4%
775.0 1
0.4%
656.4 1
0.4%
639.54 1
0.4%
631.4 1
0.4%
628.0 1
0.4%
443.6 1
0.4%
378.0 1
0.4%
350.0 1
0.4%

소재지우편번호
Text

Distinct87
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-05-11T05:45:17.399179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1845018
Min length6

Characters and Unicode

Total characters1676
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)11.1%

Sample

1st row142871
2nd row142-871
3rd row142891
4th row142875
5th row142-871
ValueCountFrequency (%)
142100 18
 
6.6%
142805 11
 
4.1%
142883 10
 
3.7%
142868 9
 
3.3%
142877 8
 
3.0%
142886 8
 
3.0%
142060 7
 
2.6%
142892 7
 
2.6%
142808 6
 
2.2%
142879 6
 
2.2%
Other values (77) 181
66.8%
2024-05-11T05:45:18.341946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 336
20.0%
2 324
19.3%
4 293
17.5%
8 293
17.5%
0 137
8.2%
7 86
 
5.1%
6 74
 
4.4%
- 50
 
3.0%
3 32
 
1.9%
5 27
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1626
97.0%
Dash Punctuation 50
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 336
20.7%
2 324
19.9%
4 293
18.0%
8 293
18.0%
0 137
8.4%
7 86
 
5.3%
6 74
 
4.6%
3 32
 
2.0%
5 27
 
1.7%
9 24
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1676
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 336
20.0%
2 324
19.3%
4 293
17.5%
8 293
17.5%
0 137
8.2%
7 86
 
5.1%
6 74
 
4.4%
- 50
 
3.0%
3 32
 
1.9%
5 27
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 336
20.0%
2 324
19.3%
4 293
17.5%
8 293
17.5%
0 137
8.2%
7 86
 
5.1%
6 74
 
4.4%
- 50
 
3.0%
3 32
 
1.9%
5 27
 
1.6%

지번주소
Text

Distinct253
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-05-11T05:45:18.976132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length36
Mean length24.236162
Min length17

Characters and Unicode

Total characters6568
Distinct characters185
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique240 ?
Unique (%)88.6%

Sample

1st row서울특별시 강북구 우이동 16-4번지
2nd row서울특별시 강북구 우이동 178-1
3rd row서울특별시 강북구 수유동 45-7번지
4th row서울특별시 강북구 수유동 484-21번지
5th row서울특별시 강북구 우이동 178-2
ValueCountFrequency (%)
서울특별시 271
22.2%
강북구 271
22.2%
미아동 110
 
9.0%
수유동 96
 
7.9%
번동 49
 
4.0%
우이동 16
 
1.3%
지하1층 6
 
0.5%
산 4
 
0.3%
522-31번지 4
 
0.3%
내 3
 
0.2%
Other values (339) 392
32.1%
2024-05-11T05:45:20.022992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1155
 
17.6%
서 287
 
4.4%
동 287
 
4.4%
북 286
 
4.4%
울 285
 
4.3%
강 283
 
4.3%
구 275
 
4.2%
시 274
 
4.2%
별 272
 
4.1%
특 271
 
4.1%
Other values (175) 2893
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3875
59.0%
Decimal Number 1252
 
19.1%
Space Separator 1155
 
17.6%
Dash Punctuation 235
 
3.6%
Close Punctuation 17
 
0.3%
Open Punctuation 17
 
0.3%
Uppercase Letter 11
 
0.2%
Other Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 287
 
7.4%
동 287
 
7.4%
북 286
 
7.4%
울 285
 
7.4%
강 283
 
7.3%
구 275
 
7.1%
시 274
 
7.1%
별 272
 
7.0%
특 271
 
7.0%
번 208
 
5.4%
Other values (150) 1147
29.6%
Decimal Number
ValueCountFrequency (%)
1 221
17.7%
2 165
13.2%
3 159
12.7%
5 140
11.2%
4 134
10.7%
7 92
7.3%
6 92
7.3%
8 88
 
7.0%
0 84
 
6.7%
9 77
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
K 3
27.3%
S 2
18.2%
Y 1
 
9.1%
B 1
 
9.1%
C 1
 
9.1%
T 1
 
9.1%
P 1
 
9.1%
A 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 4
66.7%
. 1
 
16.7%
@ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
1155
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 235
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3875
59.0%
Common 2682
40.8%
Latin 11
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 287
 
7.4%
동 287
 
7.4%
북 286
 
7.4%
울 285
 
7.4%
강 283
 
7.3%
구 275
 
7.1%
시 274
 
7.1%
별 272
 
7.0%
특 271
 
7.0%
번 208
 
5.4%
Other values (150) 1147
29.6%
Common
ValueCountFrequency (%)
1155
43.1%
- 235
 
8.8%
1 221
 
8.2%
2 165
 
6.2%
3 159
 
5.9%
5 140
 
5.2%
4 134
 
5.0%
7 92
 
3.4%
6 92
 
3.4%
8 88
 
3.3%
Other values (7) 201
 
7.5%
Latin
ValueCountFrequency (%)
K 3
27.3%
S 2
18.2%
Y 1
 
9.1%
B 1
 
9.1%
C 1
 
9.1%
T 1
 
9.1%
P 1
 
9.1%
A 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3875
59.0%
ASCII 2693
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1155
42.9%
- 235
 
8.7%
1 221
 
8.2%
2 165
 
6.1%
3 159
 
5.9%
5 140
 
5.2%
4 134
 
5.0%
7 92
 
3.4%
6 92
 
3.4%
8 88
 
3.3%
Other values (15) 212
 
7.9%
Hangul
ValueCountFrequency (%)
서 287
 
7.4%
동 287
 
7.4%
북 286
 
7.4%
울 285
 
7.4%
강 283
 
7.3%
구 275
 
7.1%
시 274
 
7.1%
별 272
 
7.0%
특 271
 
7.0%
번 208
 
5.4%
Other values (150) 1147
29.6%

도로명주소
Text

MISSING 

Distinct223
Distinct (%)92.1%
Missing29
Missing (%)10.7%
Memory size2.2 KiB
2024-05-11T05:45:20.619180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length42
Mean length28.954545
Min length21

Characters and Unicode

Total characters7007
Distinct characters194
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique206 ?
Unique (%)85.1%

Sample

1st row서울특별시 강북구 삼양로173길 12 (우이동)
2nd row서울특별시 강북구 도봉로 301 (수유동)
3rd row서울특별시 강북구 삼양로73가길 47 (수유동)
4th row서울특별시 강북구 삼양로173길 22 (우이동)
5th row서울특별시 강북구 도봉로89길 13 (수유동)
ValueCountFrequency (%)
서울특별시 242
17.9%
강북구 242
17.9%
미아동 85
 
6.3%
수유동 81
 
6.0%
번동 41
 
3.0%
도봉로 19
 
1.4%
1층 17
 
1.3%
우이동 14
 
1.0%
한천로 12
 
0.9%
인수봉로 12
 
0.9%
Other values (337) 589
43.5%
2024-05-11T05:45:21.722781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1112
 
15.9%
동 261
 
3.7%
서 258
 
3.7%
) 258
 
3.7%
( 258
 
3.7%
북 256
 
3.7%
울 256
 
3.7%
강 253
 
3.6%
시 246
 
3.5%
구 246
 
3.5%
Other values (184) 3603
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4196
59.9%
Space Separator 1112
 
15.9%
Decimal Number 1035
 
14.8%
Close Punctuation 258
 
3.7%
Open Punctuation 258
 
3.7%
Other Punctuation 115
 
1.6%
Dash Punctuation 20
 
0.3%
Uppercase Letter 12
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 261
 
6.2%
서 258
 
6.1%
북 256
 
6.1%
울 256
 
6.1%
강 253
 
6.0%
시 246
 
5.9%
구 246
 
5.9%
로 246
 
5.9%
별 243
 
5.8%
특 242
 
5.8%
Other values (159) 1689
40.3%
Decimal Number
ValueCountFrequency (%)
1 246
23.8%
2 140
13.5%
4 110
10.6%
9 91
 
8.8%
3 87
 
8.4%
0 86
 
8.3%
5 82
 
7.9%
7 80
 
7.7%
8 57
 
5.5%
6 56
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
B 3
25.0%
K 3
25.0%
S 2
16.7%
A 1
 
8.3%
P 1
 
8.3%
T 1
 
8.3%
Y 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 107
93.0%
. 7
 
6.1%
@ 1
 
0.9%
Space Separator
ValueCountFrequency (%)
1112
100.0%
Close Punctuation
ValueCountFrequency (%)
) 258
100.0%
Open Punctuation
ValueCountFrequency (%)
( 258
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4196
59.9%
Common 2799
39.9%
Latin 12
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 261
 
6.2%
서 258
 
6.1%
북 256
 
6.1%
울 256
 
6.1%
강 253
 
6.0%
시 246
 
5.9%
구 246
 
5.9%
로 246
 
5.9%
별 243
 
5.8%
특 242
 
5.8%
Other values (159) 1689
40.3%
Common
ValueCountFrequency (%)
1112
39.7%
) 258
 
9.2%
( 258
 
9.2%
1 246
 
8.8%
2 140
 
5.0%
4 110
 
3.9%
, 107
 
3.8%
9 91
 
3.3%
3 87
 
3.1%
0 86
 
3.1%
Other values (8) 304
 
10.9%
Latin
ValueCountFrequency (%)
B 3
25.0%
K 3
25.0%
S 2
16.7%
A 1
 
8.3%
P 1
 
8.3%
T 1
 
8.3%
Y 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4196
59.9%
ASCII 2811
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1112
39.6%
) 258
 
9.2%
( 258
 
9.2%
1 246
 
8.8%
2 140
 
5.0%
4 110
 
3.9%
, 107
 
3.8%
9 91
 
3.2%
3 87
 
3.1%
0 86
 
3.1%
Other values (15) 316
 
11.2%
Hangul
ValueCountFrequency (%)
동 261
 
6.2%
서 258
 
6.1%
북 256
 
6.1%
울 256
 
6.1%
강 253
 
6.0%
시 246
 
5.9%
구 246
 
5.9%
로 246
 
5.9%
별 243
 
5.8%
특 242
 
5.8%
Other values (159) 1689
40.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct121
Distinct (%)50.2%
Missing30
Missing (%)11.1%
Infinite0
Infinite (%)0.0%
Mean1116.7759
Minimum1000
Maximum1237
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T05:45:22.151669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1007
Q11053
median1115
Q31181
95-th percentile1229
Maximum1237
Range237
Interquartile range (IQR)128

Descriptive statistics

Standard deviation72.061776
Coefficient of variation (CV)0.06452662
Kurtosis-1.2944453
Mean1116.7759
Median Absolute Deviation (MAD)64
Skewness0.019960839
Sum269143
Variance5192.8996
MonotonicityNot monotonic
2024-05-11T05:45:22.760996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1041 8
 
3.0%
1137 7
 
2.6%
1225 5
 
1.8%
1095 5
 
1.8%
1058 5
 
1.8%
1014 4
 
1.5%
1233 4
 
1.5%
1141 4
 
1.5%
1133 4
 
1.5%
1158 4
 
1.5%
Other values (111) 191
70.5%
(Missing) 30
 
11.1%
ValueCountFrequency (%)
1000 2
0.7%
1001 1
 
0.4%
1002 3
1.1%
1003 1
 
0.4%
1005 3
1.1%
1006 2
0.7%
1007 2
0.7%
1012 4
1.5%
1014 4
1.5%
1015 2
0.7%
ValueCountFrequency (%)
1237 3
1.1%
1233 4
1.5%
1232 2
 
0.7%
1231 1
 
0.4%
1230 2
 
0.7%
1229 2
 
0.7%
1226 1
 
0.4%
1225 5
1.8%
1224 2
 
0.7%
1215 2
 
0.7%

사업장명
Text

Distinct251
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-05-11T05:45:23.246071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length15
Mean length7.6937269
Min length3

Characters and Unicode

Total characters2085
Distinct characters275
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique232 ?
Unique (%)85.6%

Sample

1st row제일은행연수원
2nd row삼양교통
3rd row대한병원
4th row한빛맹아원
5th row영신여객
ValueCountFrequency (%)
어린이집 14
 
4.3%
구립 9
 
2.7%
주식회사 4
 
1.2%
앙팡어린이집 3
 
0.9%
번동3단지종합사회복지관 2
 
0.6%
요양병원 2
 
0.6%
사단법인 2
 
0.6%
구세군강북어린이집 2
 
0.6%
유치원 2
 
0.6%
꿈나무어린이집 2
 
0.6%
Other values (270) 286
87.2%
2024-05-11T05:45:24.236959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 128
 
6.1%
집 112
 
5.4%
어 110
 
5.3%
린 109
 
5.2%
원 67
 
3.2%
57
 
2.7%
교 46
 
2.2%
학 43
 
2.1%
북 43
 
2.1%
강 36
 
1.7%
Other values (265) 1334
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1986
95.3%
Space Separator 57
 
2.7%
Close Punctuation 12
 
0.6%
Open Punctuation 12
 
0.6%
Uppercase Letter 7
 
0.3%
Decimal Number 6
 
0.3%
Lowercase Letter 4
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 128
 
6.4%
집 112
 
5.6%
어 110
 
5.5%
린 109
 
5.5%
원 67
 
3.4%
교 46
 
2.3%
학 43
 
2.2%
북 43
 
2.2%
강 36
 
1.8%
유 36
 
1.8%
Other values (251) 1256
63.2%
Uppercase Letter
ValueCountFrequency (%)
T 3
42.9%
K 2
28.6%
E 1
 
14.3%
H 1
 
14.3%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
3 2
33.3%
5 1
16.7%
1 1
16.7%
Lowercase Letter
ValueCountFrequency (%)
s 2
50.0%
k 2
50.0%
Space Separator
ValueCountFrequency (%)
57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1986
95.3%
Common 88
 
4.2%
Latin 11
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 128
 
6.4%
집 112
 
5.6%
어 110
 
5.5%
린 109
 
5.5%
원 67
 
3.4%
교 46
 
2.3%
학 43
 
2.2%
북 43
 
2.2%
강 36
 
1.8%
유 36
 
1.8%
Other values (251) 1256
63.2%
Common
ValueCountFrequency (%)
57
64.8%
) 12
 
13.6%
( 12
 
13.6%
2 2
 
2.3%
3 2
 
2.3%
. 1
 
1.1%
5 1
 
1.1%
1 1
 
1.1%
Latin
ValueCountFrequency (%)
T 3
27.3%
s 2
18.2%
k 2
18.2%
K 2
18.2%
E 1
 
9.1%
H 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1986
95.3%
ASCII 99
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 128
 
6.4%
집 112
 
5.6%
어 110
 
5.5%
린 109
 
5.5%
원 67
 
3.4%
교 46
 
2.3%
학 43
 
2.2%
북 43
 
2.2%
강 36
 
1.8%
유 36
 
1.8%
Other values (251) 1256
63.2%
ASCII
ValueCountFrequency (%)
57
57.6%
) 12
 
12.1%
( 12
 
12.1%
T 3
 
3.0%
2 2
 
2.0%
s 2
 
2.0%
k 2
 
2.0%
3 2
 
2.0%
K 2
 
2.0%
. 1
 
1.0%
Other values (4) 4
 
4.0%

최종수정일자
Date

Distinct262
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum2001-11-15 00:00:00
Maximum2024-04-25 14:12:17
2024-05-11T05:45:24.723657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:45:25.243152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
I
136 
U
135 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowU
3rd rowI
4th rowI
5th rowU

Common Values

ValueCountFrequency (%)
I 136
50.2%
U 135
49.8%

Length

2024-05-11T05:45:25.756472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:26.187646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 136
50.2%
u 135
49.8%

데이터갱신일자
Date

Distinct99
Distinct (%)36.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:07:00
2024-05-11T05:45:26.566562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:45:27.210844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct9
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
어린이집
108 
집단급식소
50 
학교
37 
병원
22 
산업체
19 
Other values (4)
35 

Length

Max length8
Median length6
Mean length3.8856089
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row집단급식소
2nd row산업체
3rd row병원
4th row사회복지시설
5th row산업체

Common Values

ValueCountFrequency (%)
어린이집 108
39.9%
집단급식소 50
18.5%
학교 37
 
13.7%
병원 22
 
8.1%
산업체 19
 
7.0%
사회복지시설 19
 
7.0%
공공기관 9
 
3.3%
기타 집단급식소 5
 
1.8%
수련원 2
 
0.7%

Length

2024-05-11T05:45:27.745739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:28.168297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이집 108
39.1%
집단급식소 55
19.9%
학교 37
 
13.4%
병원 22
 
8.0%
산업체 19
 
6.9%
사회복지시설 19
 
6.9%
공공기관 9
 
3.3%
기타 5
 
1.8%
수련원 2
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct201
Distinct (%)77.3%
Missing11
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean201950.28
Minimum200234.13
Maximum204089.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T05:45:28.628166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200234.13
5-th percentile200806.25
Q1201248.27
median201851.71
Q3202547.17
95-th percentile203529.29
Maximum204089.67
Range3855.541
Interquartile range (IQR)1298.8946

Descriptive statistics

Standard deviation858.61912
Coefficient of variation (CV)0.0042516363
Kurtosis-0.53529286
Mean201950.28
Median Absolute Deviation (MAD)664.82772
Skewness0.36658927
Sum52507072
Variance737226.79
MonotonicityNot monotonic
2024-05-11T05:45:29.102331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202582.466293771 4
 
1.5%
203757.285284697 4
 
1.5%
200638.95596294 4
 
1.5%
201411.608254475 3
 
1.1%
201754.54815064 3
 
1.1%
201114.247717132 3
 
1.1%
202383.132104985 3
 
1.1%
201415.810112604 3
 
1.1%
201474.106292996 3
 
1.1%
202728.713288169 2
 
0.7%
Other values (191) 228
84.1%
(Missing) 11
 
4.1%
ValueCountFrequency (%)
200234.13213979 1
 
0.4%
200411.014317944 2
0.7%
200482.783195425 2
0.7%
200496.863719013 1
 
0.4%
200638.95596294 4
1.5%
200671.098692403 2
0.7%
200704.539774217 1
 
0.4%
200811.606913557 1
 
0.4%
200814.185606777 1
 
0.4%
200827.985680041 1
 
0.4%
ValueCountFrequency (%)
204089.673173372 2
0.7%
204062.351684236 1
 
0.4%
203932.991517795 2
0.7%
203895.660018622 1
 
0.4%
203757.285284697 4
1.5%
203641.115663588 1
 
0.4%
203627.347902029 2
0.7%
203524.134017455 1
 
0.4%
203393.542019461 1
 
0.4%
203376.491722308 1
 
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct201
Distinct (%)77.3%
Missing11
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean458863.31
Minimum456473.89
Maximum462569.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T05:45:29.532997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456473.89
5-th percentile456958.01
Q1457863.6
median458844.2
Q3459744.67
95-th percentile461317.73
Maximum462569.13
Range6095.2456
Interquartile range (IQR)1881.0782

Descriptive statistics

Standard deviation1324.1853
Coefficient of variation (CV)0.0028857946
Kurtosis-0.14725917
Mean458863.31
Median Absolute Deviation (MAD)940.37838
Skewness0.44911656
Sum1.1930446 × 108
Variance1753466.6
MonotonicityNot monotonic
2024-05-11T05:45:30.013141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
459530.486138019 4
 
1.5%
458490.883652834 4
 
1.5%
459610.253323515 4
 
1.5%
460154.503828252 3
 
1.1%
460446.862089418 3
 
1.1%
458148.769735117 3
 
1.1%
456824.739956011 3
 
1.1%
460024.404015615 3
 
1.1%
457160.754308789 3
 
1.1%
458139.375888163 2
 
0.7%
Other values (191) 228
84.1%
(Missing) 11
 
4.1%
ValueCountFrequency (%)
456473.886142136 1
 
0.4%
456717.319421348 1
 
0.4%
456774.967987942 1
 
0.4%
456792.018736677 2
0.7%
456807.176895604 1
 
0.4%
456824.739956011 3
1.1%
456845.373829971 1
 
0.4%
456850.973447567 1
 
0.4%
456875.973976242 1
 
0.4%
456898.788065585 1
 
0.4%
ValueCountFrequency (%)
462569.131785221 1
0.4%
462416.392839185 1
0.4%
462330.157309548 1
0.4%
462321.891621268 1
0.4%
462237.573145694 2
0.7%
462056.904998381 1
0.4%
461880.880559769 1
0.4%
461793.458013575 1
0.4%
461741.554943103 1
0.4%
461687.606038005 2
0.7%

위생업태명
Categorical

Distinct10
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
어린이집
79 
<NA>
67 
집단급식소
50 
학교
32 
병원
15 
Other values (5)
28 

Length

Max length8
Median length4
Mean length3.9298893
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row집단급식소
2nd row<NA>
3rd row병원
4th row사회복지시설
5th row<NA>

Common Values

ValueCountFrequency (%)
어린이집 79
29.2%
<NA> 67
24.7%
집단급식소 50
18.5%
학교 32
11.8%
병원 15
 
5.5%
사회복지시설 14
 
5.2%
공공기관 6
 
2.2%
산업체 5
 
1.8%
수련원 2
 
0.7%
기타 집단급식소 1
 
0.4%

Length

2024-05-11T05:45:30.408769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:30.789387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이집 79
29.0%
na 67
24.6%
집단급식소 51
18.8%
학교 32
11.8%
병원 15
 
5.5%
사회복지시설 14
 
5.1%
공공기관 6
 
2.2%
산업체 5
 
1.8%
수련원 2
 
0.7%
기타 1
 
0.4%

남성종사자수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
221 
0
50 

Length

Max length4
Median length4
Mean length3.4464945
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 221
81.5%
0 50
 
18.5%

Length

2024-05-11T05:45:31.252941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:31.581531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 221
81.5%
0 50
 
18.5%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
221 
0
49 
7
 
1

Length

Max length4
Median length4
Mean length3.4464945
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 221
81.5%
0 49
 
18.1%
7 1
 
0.4%

Length

2024-05-11T05:45:31.956642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:32.247784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 221
81.5%
0 49
 
18.1%
7 1
 
0.4%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
227 
기타
30 
주택가주변
 
8
학교정화(절대)
 
3
아파트지역
 
2

Length

Max length8
Median length4
Mean length3.8745387
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row기타
2nd row<NA>
3rd row기타
4th row기타
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 227
83.8%
기타 30
 
11.1%
주택가주변 8
 
3.0%
학교정화(절대) 3
 
1.1%
아파트지역 2
 
0.7%
학교정화(상대) 1
 
0.4%

Length

2024-05-11T05:45:32.556798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:33.023922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 227
83.8%
기타 30
 
11.1%
주택가주변 8
 
3.0%
학교정화(절대 3
 
1.1%
아파트지역 2
 
0.7%
학교정화(상대 1
 
0.4%

등급구분명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
227 
기타
44 

Length

Max length4
Median length4
Mean length3.6752768
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row<NA>
3rd row기타
4th row기타
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 227
83.8%
기타 44
 
16.2%

Length

2024-05-11T05:45:33.300810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:33.577217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 227
83.8%
기타 44
 
16.2%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
상수도전용
158 
<NA>
113 

Length

Max length5
Median length5
Mean length4.5830258
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상수도전용
2nd row<NA>
3rd row상수도전용
4th row상수도전용
5th row<NA>

Common Values

ValueCountFrequency (%)
상수도전용 158
58.3%
<NA> 113
41.7%

Length

2024-05-11T05:45:33.891996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:34.223611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 158
58.3%
na 113
41.7%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
258 
0
 
13

Length

Max length4
Median length4
Mean length3.8560886
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 258
95.2%
0 13
 
4.8%

Length

2024-05-11T05:45:34.639271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:34.995728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 258
95.2%
0 13
 
4.8%

본사종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
179 
0
83 
1
 
6
2
 
2
4
 
1

Length

Max length4
Median length4
Mean length2.9815498
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 179
66.1%
0 83
30.6%
1 6
 
2.2%
2 2
 
0.7%
4 1
 
0.4%

Length

2024-05-11T05:45:35.336082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:35.649647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 179
66.1%
0 83
30.6%
1 6
 
2.2%
2 2
 
0.7%
4 1
 
0.4%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
258 
0
 
13

Length

Max length4
Median length4
Mean length3.8560886
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 258
95.2%
0 13
 
4.8%

Length

2024-05-11T05:45:36.231082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:36.484028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 258
95.2%
0 13
 
4.8%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
258 
0
 
13

Length

Max length4
Median length4
Mean length3.8560886
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 258
95.2%
0 13
 
4.8%

Length

2024-05-11T05:45:36.777942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:37.085961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 258
95.2%
0 13
 
4.8%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
258 
0
 
13

Length

Max length4
Median length4
Mean length3.8560886
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 258
95.2%
0 13
 
4.8%

Length

2024-05-11T05:45:37.386965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:37.666694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 258
95.2%
0 13
 
4.8%

건물소유구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
261 
자가
 
10

Length

Max length4
Median length4
Mean length3.9261993
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 261
96.3%
자가 10
 
3.7%

Length

2024-05-11T05:45:38.001663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:38.324843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 261
96.3%
자가 10
 
3.7%

보증액
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
230 
0
41 

Length

Max length4
Median length4
Mean length3.5461255
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 230
84.9%
0 41
 
15.1%

Length

2024-05-11T05:45:38.669788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:38.997530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 230
84.9%
0 41
 
15.1%

월세액
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
230 
0
41 

Length

Max length4
Median length4
Mean length3.5461255
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 230
84.9%
0 41
 
15.1%

Length

2024-05-11T05:45:39.381862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:45:39.728746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 230
84.9%
0 41
 
15.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing67
Missing (%)24.7%
Memory size674.0 B
False
204 
(Missing)
67 
ValueCountFrequency (%)
False 204
75.3%
(Missing) 67
 
24.7%
2024-05-11T05:45:40.022066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct143
Distinct (%)70.1%
Missing67
Missing (%)24.7%
Infinite0
Infinite (%)0.0%
Mean85.778725
Minimum0
Maximum978.12
Zeros39
Zeros (%)14.4%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T05:45:40.385244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.805
median22.6
Q3101.075
95-th percentile370.988
Maximum978.12
Range978.12
Interquartile range (IQR)94.27

Descriptive statistics

Standard deviation141.00631
Coefficient of variation (CV)1.6438378
Kurtosis10.291403
Mean85.778725
Median Absolute Deviation (MAD)22.6
Skewness2.7987183
Sum17498.86
Variance19882.779
MonotonicityNot monotonic
2024-05-11T05:45:40.821930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 39
 
14.4%
16.5 4
 
1.5%
5.0 3
 
1.1%
12.0 3
 
1.1%
14.0 3
 
1.1%
7.0 3
 
1.1%
22.6 2
 
0.7%
63.0 2
 
0.7%
13.0 2
 
0.7%
200.0 2
 
0.7%
Other values (133) 141
52.0%
(Missing) 67
24.7%
ValueCountFrequency (%)
0.0 39
14.4%
3.74 1
 
0.4%
4.4 1
 
0.4%
4.59 1
 
0.4%
4.94 1
 
0.4%
5.0 3
 
1.1%
6.0 1
 
0.4%
6.16 1
 
0.4%
6.58 1
 
0.4%
6.6 1
 
0.4%
ValueCountFrequency (%)
978.12 1
0.4%
706.15 1
0.4%
620.64 1
0.4%
492.65 1
0.4%
489.6 1
0.4%
465.0 1
0.4%
460.44 1
0.4%
431.0 1
0.4%
408.0 1
0.4%
406.22 1
0.4%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing271
Missing (%)100.0%
Memory size2.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing271
Missing (%)100.0%
Memory size2.5 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing271
Missing (%)100.0%
Memory size2.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030800003080000-105-1990-0003319900302<NA>3폐업2폐업20080624<NA><NA><NA>02 9932631102.0142871서울특별시 강북구 우이동 16-4번지<NA><NA>제일은행연수원2003-06-11 00:00:00I2018-08-31 23:59:59.0집단급식소201012.909062462237.573146집단급식소00기타기타상수도전용<NA>0<NA><NA><NA><NA><NA><NA>N315.16<NA><NA><NA>
130800003080000-105-1990-000341990-03-02<NA>1영업/정상1영업<NA><NA><NA><NA>02 904 057223.0142-871서울특별시 강북구 우이동 178-1서울특별시 강북구 삼양로173길 12 (우이동)1002삼양교통2024-04-12 10:14:53U2023-12-03 23:04:00.0산업체200970.97412462330.15731<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
230800003080000-105-1990-0003619900302<NA>1영업/정상1영업<NA><NA><NA><NA>02 903323197.47142891서울특별시 강북구 수유동 45-7번지서울특별시 강북구 도봉로 301 (수유동)1081대한병원2017-01-09 16:09:20I2018-08-31 23:59:59.0병원201952.090792459227.557988병원00기타기타상수도전용<NA>0<NA><NA><NA><NA><NA><NA>N226.35<NA><NA><NA>
330800003080000-105-1990-0003719900302<NA>1영업/정상1영업<NA><NA><NA><NA>02 989601730.0142875서울특별시 강북구 수유동 484-21번지서울특별시 강북구 삼양로73가길 47 (수유동)1103한빛맹아원2017-07-12 13:46:08I2018-08-31 23:59:59.0사회복지시설201316.076857458415.424078사회복지시설00기타기타상수도전용<NA>0<NA><NA><NA><NA><NA><NA>N162.0<NA><NA><NA>
430800003080000-105-1990-000381990-03-02<NA>1영업/정상1영업<NA><NA><NA><NA>02 996350116.8142-871서울특별시 강북구 우이동 178-2서울특별시 강북구 삼양로173길 22 (우이동)1002영신여객2024-04-12 09:53:45U2023-12-03 23:04:00.0산업체200903.303747462321.891621<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
530800003080000-105-1990-0003919900302<NA>3폐업2폐업19981219<NA><NA><NA>02 994286523.36142060서울특별시 강북구 번동 산 456-0번지<NA><NA>신진자동차학원2002-01-02 00:00:00I2018-08-31 23:59:59.0집단급식소<NA><NA>집단급식소00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N90.46<NA><NA><NA>
630800003080000-105-1990-0004019900302<NA>3폐업2폐업20000721<NA><NA><NA>02 425368043.86142100서울특별시 강북구 미아동 산 62-28번지<NA><NA>새한병원2002-01-02 00:00:00I2018-08-31 23:59:59.0집단급식소<NA><NA>집단급식소00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N86.36<NA><NA><NA>
730800003080000-105-1990-0004119900302<NA>3폐업2폐업20040421<NA><NA><NA>02 902390632.1142883서울특별시 강북구 수유동 522-31번지<NA><NA>새마을금고연합회중앙교육원2001-11-15 00:00:00I2018-08-31 23:59:59.0집단급식소200638.955963459610.253324집단급식소00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N279.59<NA><NA><NA>
830800003080000-105-1990-0004219900302<NA>1영업/정상1영업<NA><NA><NA><NA>02 903636050.0142878서울특별시 강북구 수유동 192-59번지서울특별시 강북구 도봉로89길 13 (수유동)1071강북구청후생복지원2017-07-11 16:46:25I2018-08-31 23:59:59.0공공기관202178.772316459687.049923공공기관00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N172.7<NA><NA><NA>
930800003080000-105-1990-000431990-03-02<NA>1영업/정상1영업<NA><NA><NA><NA>02 981900125.37142-060서울특별시 강북구 번동 375-0서울특별시 강북구 한천로 939 (번동)1137한성운수(주)2023-04-07 15:59:57U2022-12-04 00:09:00.0산업체203013.040176459085.802957<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
26130800003080000-105-2021-000122021-07-26<NA>1영업/정상1영업<NA><NA><NA><NA>02 34085000183.33142-090서울특별시 강북구 우이동 346 파라스파라 서울서울특별시 강북구 삼양로 689, 파라스파라 서울 114동 지하1층 (우이동)1000파라스파라 서울2024-04-12 10:00:53U2023-12-03 23:04:00.0산업체200704.539774462416.392839<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26230800003080000-105-2021-0001320210915<NA>1영업/정상1영업<NA><NA><NA><NA><NA>45.7142884서울특별시 강북구 수유동 409-6 서울우이초등학교서울특별시 강북구 삼양로99길 36, 서울우이초등학교 5층 (수유동)1085서울우이유치원2022-10-20 09:48:46U2021-10-30 22:02:00.0어린이집201248.270386459568.353614<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26330800003080000-105-2022-000012022-02-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>142-883서울특별시 강북구 수유동 553-61 신극동유치원서울특별시 강북구 인수봉로 260, 신극동유치원 (수유동)1032길물빛유치원2024-04-15 09:27:42U2023-12-03 23:07:00.0어린이집200996.748132459945.147477<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26430800003080000-105-2022-000022022-04-12<NA>3폐업2폐업2023-02-28<NA><NA><NA><NA>4.95142-886서울특별시 강북구 수유동 472-29 꿈나무어린이집서울특별시 강북구 삼양로85길 4, 꿈나무어린이집 (수유동)1098꿈나무어린이집2023-02-28 14:02:06U2022-12-03 00:03:00.0어린이집201444.913994459025.593116<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26530800003080000-105-2022-000032022-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>198.0142-812서울특별시 강북구 미아동 304-7 성신병원서울특별시 강북구 도봉로 181 (미아동)1170경희황소한방병원2024-04-15 09:28:05U2023-12-03 23:07:00.0병원202253.635126458066.882225<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26630800003080000-105-2022-000042022-05-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>22.84142-070서울특별시 강북구 수유동 558-32 지하1층서울특별시 강북구 인수봉로 298, B1층 (수유동)1027사단법인 삼각산재미난마을 부설 대안교육기관 삼각산재미난2024-04-15 09:28:22U2023-12-03 23:07:00.0학교200890.650322460335.867186<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26730800003080000-105-2022-0000520220627<NA>3폐업2폐업20220922<NA><NA><NA><NA>0.0142883서울특별시 강북구 수유동 522 서울 영어마을 수유캠프서울특별시 강북구 삼각산로 43, 서울 영어마을 수유캠프 (수유동)1019서울영어마을수유캠프2022-09-22 10:18:36U2021-12-08 22:04:00.0기타 집단급식소200671.098692459744.674161<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26830800003080000-105-2022-0000620220902<NA>1영업/정상1영업<NA><NA><NA><NA>02997 58710.0142887서울특별시 강북구 수유동 535-244 선일교통(주)서울특별시 강북구 4.19로 84, 선일교통(주) 1층 (수유동)1012선일교통(주)2022-09-02 16:33:34I2021-12-09 00:04:00.0산업체200411.014318460324.845105<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26930800003080000-105-2022-000072022-12-30<NA>1영업/정상1영업<NA><NA><NA><NA>02987 6646250.3142-706서울특별시 강북구 번동 239 강북유니온빌딩 지하1층서울특별시 강북구 한천로109길 10, 강북유니온빌딩 B1층 (번동)1225강북집단화사업협동조합2024-04-12 10:03:05U2023-12-03 23:04:00.0산업체203757.285285458490.883653<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27030800003080000-105-2023-000012023-03-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>142-802서울특별시 강북구 미아동 4 꿈의숲 롯데캐슬서울특별시 강북구 오현로 56, 관리동 1층 (미아동, 꿈의숲 롯데캐슬)1232구립꿈의숲캐슬어린이집2024-04-25 14:12:17U2023-12-03 22:07:00.0어린이집203160.494747457237.260771<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>